A5002110350- Additive Manufacturing Materials and Processes
- Additive Manufacturing and 3D Printing Technologies
- Manufacturing Process and Optimization
- High Entropy Alloys Studies
- Material Properties and Processing
- Numerical methods in engineering
- Composite Material Mechanics
- Titanium Alloys Microstructure and Properties
- Hydraulic and Pneumatic Systems
- Advanced Mathematical Modeling in Engineering
- Textile materials and evaluations
- Welding Techniques and Residual Stresses
- Advanced Semiconductor Detectors and Materials
- Model Reduction and Neural Networks
- Probabilistic and Robust Engineering Design
- Mechanical Behavior of Composites
- Injection Molding Process and Properties
Northwestern University
2019-2021
Abstract Multi-scale, multi-physics, computational models are a promising tool to provide detailed insights understand the process–structure–property–performance relationships in additive manufacturing (AM) processes. To take advantage of strengths both physics-based and data-driven models, we propose novel, hybrid modeling framework for laser powder bed fusion (L-PBF) process. Our unbiased model-integration method combines physics-based, simulation data, measurement data approaching more...
Abstract Laser powder-bed fusion is an additive manufacturing (AM) process that offers exciting advantages for the fabrication of metallic parts compared to traditional techniques, such as ability create complex geometries with less material waste. However, intricacy and extreme cyclic heating cooling leads defects variations in mechanical properties; this often results unpredictable even inferior performance additively manufactured materials. Key indicators potential a fabricated part are...
Abstract Multi-scale, multi-physics, computational models are a promising tool to provide detailed insights understand the process-structure-property-performance relationships in additive manufacturing (AM) processes. To take advantage of strengths both physics-based and data-driven models, we propose novel, hybrid modeling framework for laser powder bed fusion (L-PBF) Our unbiased, model integration method combines data measurement approaching more accurate prediction melt-pool width. Both...
Abstract Tremendous efforts have been made to use computational and simulation models of additive manufacturing (AM) processes. The goals these are better understand process complexities realize high-quality parts. However, understanding whether any model is a correct representation for given scenario difficult proposition. For example, when using metal powders, the laser powder-bed fusion (L-PBF) involves complex physical phenomena such as powder morphology, heat transfer, phase...